A diagnostic biomarker profile for fibromyalgia syndrome based on an NMR metabolomics study of selected patients and controls

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Abstract

Background:
Fibromyalgia syndrome (FMS) is a chronic pain syndrome. A plausible pathogenesis of the disease is
uncertain and the pursuit of measurable biomarkers for objective identification of affected individuals is a continuing
endeavour in FMS research. Our objective was to perform an explorative metabolomics study (1) to elucidate the
global urinary metabolite profile of patients suffering from FMS, and (2) to explore the potential of this metabolite
information to augment existing medical practice in diagnosing the disease.
Methods:
We selected patients with a medical history of persistent FMS (
n
= 18), who described their recent state of
the disease through the Fibromyalgia Impact Questionnaire (FIQR) and an in-house clinical questionnaire (IHCQ). Three
control groups were used: first-generation family members of the patients (
n
= 11), age-related individuals without any
indications of FMS or related conditions (
n
= 10), and healthy young (18
–
22 years) individuals (
n
=20).All
subjects were female and the biofluid under investigation was urine. Correlation analysis of the FIQR showed
the FMS patients represented a well-defined disease gro
up for this metabolomics study. Spectral analyses of
urine were conducted using a 500 MHz
1
H nuclear magnetic resonance (NMR) spectrometer; data processing
and analyses were performed using Matlab, R, SPSS and SAS software.
Results and discussion:
Unsupervised and supervised multivariate analyses distinguished all three control groups and
the FMS patients, and significant increases in metabolites related to the gut microbiome (hippuric, succinic and lactic
acids) were observed. We have developed an algorithm f
or the diagnosis of FMS consisting of three metabolites
—
succinic acid, taurine and creatine
—
that have a good level of diagnostic accurac
y (Receiver Operating Characteristic
(ROC) analysis
—
area under the curve 90%) and on the pain and fatigue symptoms for the selected FMS patient group.
Conclusion:
Our data and comparative analyses indicated an altere
d metabolic profile of patients with FMS, analytically
detectable within their urine. Validation studies may substantiate urinary metabolites to supplement information from
medical assessment, tender-point measurements and FIQR questionnaires for an improved objective diagnosis of FMS